It is widely acknowledged that traditional Project Management techniques are no longer sufficient, as projects become more complex and client's demand reduced timescales. Problems that arise include inadequate planning and risk analysis, ineffective project monitoring and control, and uninformed post-mortem analysis. Effective modelling techniques, which capture the complexities of such projects, are therefore necessary for adequate project management. This book looks at those issues, describes some modelling techniques, then discusses their merits and possible synthesis. This is the only project management book that deals with Project Modelling. Features case studies throughout. Places the various approaches to Project Modelling within a coherent framework, and gives an objective overview.

Table of Contents:
1 This Book 1 Introduction to the book and the author 1 Why is there a need for this book? 3 The structure of this book 7 What do I need to know before I read this book? 8 Conclusion 11 2 Projects 13 What is a project? 13 What are project objectives? 15 Basic project management techniques 18 Projects referred to in this book 23 Conclusion 29 3 Modelling 31 What is a model? 31 Why do we model? 35 Modelling in practice 40 Validation 44 Conclusion 47 4 What is a Complex Project? 49 Introduction 49 What is complexity? Structural complexity 50 What is complexity? Uncertainty 55 What is complexity? Summary 58 Increasing complexity 59 Tools and techniques—and the way ahead 62 5 Discrete Effects and Uncertainty 65 Introduction 65 Uncertainty and risk in projects 66 Cost risk: additive calculations 78 Time risk: effects in a network 89 Analysing time risk: simulation 96 Criticality and cruciality 104 The three criteria and beyond 115 Conclusion 118 6 Discrete Effects: Collecting Data 119 Introduction 119 Collecting subjective data: identification 121 Collecting subjective data: general principles of quantification 123 Collecting subjective data: simple activity-duration models 126 Effect of targets 131 Conclusion 136 7 The Soft Effects 137 Introduction 137 Some key project characteristics 139 Client behaviour and external effects on the project 140 Management decisions 146 Project staffing 149 Subjective effects within the project 151 Summary and looking forward 154 8 Systemic Effects 155 The effects 155 A brief introduction to cause mapping 157 Qualitative modelling: simple compounding 158 Qualitative modelling: loops 161 Quantitative modelling 163 9 System Dynamics Modelling 167 Introduction to system dynamics 167 Using system dynamics with mapping 171 Elements of models 175 Production elements 176 Other elements 188 Managerial actions 189 How effects compound 193 Validation 195 Conclusion 196 10 Hybrid Methods: The Way Forward? 199 Introduction 199 Adapting standard models using lessons learned from SD 200 Using conventional tools to generate SD models 205 Using SD and conventional models to inform each other 206 Extending SD: discrete events and stochastic SD 208 The need for intelligence 210 Conclusion 212 11 The Role of the Modeller 215 Introduction 215 Project management 215 What makes a good modeller? 217 Stages of project modelling 219 Chapter summary 230 12 Conclusion 233 Appendix: Extension of time claims 235 References 249 Index 265